scholarly journals Fuzzy waste load allocation model: a multiobjective approach

2009 ◽  
Vol 12 (1) ◽  
pp. 83-96 ◽  
Author(s):  
Subimal Ghosh ◽  
P. P. Mujumdar
Keyword(s):  
Water Quality ◽  
Goal Programming ◽  
Optimization Model ◽  
River System ◽  
Base Flow ◽  
Risk Minimization ◽  
Waste Load Allocation ◽  
Allocation Model ◽  
Waste Load ◽  
Input Variables

Fuzzy Waste Load Allocation Model (FWLAM), developed in an earlier study, derives the optimal fractional levels, for the base flow conditions, considering the goals of the Pollution Control Agency (PCA) and dischargers. The Modified Fuzzy Waste Load Allocation Model (MFWLAM) developed subsequently is a stochastic model and considers the moments (mean, variance and skewness) of water quality indicators, incorporating uncertainty due to randomness of input variables along with uncertainty due to imprecision. The risk of low water quality is reduced significantly by using this modified model, but inclusion of new constraints leads to a low value of acceptability level, λ, interpreted as the maximized minimum satisfaction in the system. To improve this value, a new model, which is a combination of FWLAM and MFWLAM, is presented, allowing for some violations in the constraints of MFWLAM. This combined model is a multiobjective optimization model having the objectives, maximization of acceptability level and minimization of violation of constraints. Fuzzy multiobjective programming, goal programming and fuzzy goal programming are used to find the solutions. For the optimization model, Probabilistic Global Search Lausanne (PGSL) is used as a nonlinear optimization tool. The methodology is applied to a case study of the Tunga–Bhadra river system in south India. The model results in a compromised solution of a higher value of acceptability level as compared to MFWLAM, with a satisfactory value of risk. Thus the goal of risk minimization is achieved with a comparatively better value of acceptability level.

Development of a Waste Load Allocation Model for the Charleston Harbor Estuary, Phase II: Water Quality

2000 ◽  
Vol 50 (1) ◽  
pp. 99-107 ◽  
Author(s):  
E.A. Yassuda ◽  
S.R. Davie ◽  
D.L. Mendelsohn ◽  
T. Isaji ◽  
S.J. Peene
Keyword(s):  
Water Quality ◽  
Phase Ii ◽  
Waste Load Allocation ◽  
Allocation Model ◽  
Waste Load

Multi-objective multi-pollutant waste load allocation model for rivers using coupled archived simulated annealing algorithm with QUAL2Kw

2019 ◽  
Vol 21 (3) ◽  
pp. 397-410 ◽  
Author(s):  
Motahareh Saadatpour ◽  
Abbas Afshar ◽  
Helaleh Khoshkam
Keyword(s):  
Water Quality ◽  
Simulated Annealing ◽  
Water Quality Index ◽  
Quality Index ◽  
Transport Processes ◽  
Optimization Approach ◽  
Waste Load Allocation ◽  
Allocation Model ◽  
Multi Objective ◽  
Waste Load

Abstract A simulation-optimization approach is a suitable tool in waste load allocation problems when considering competing objectives and complex pollutant fate and transport processes in water bodies. Here, an archived multi-objective simulated annealing (AMOSA) algorithm is developed to determine various decision variables related to multi-pollutant waste load allocation (MPWLA) problems. The developed AMOSA algorithm has been coupled to QUAL2Kw in order to derive optimal MPWLA programs in Gheshlagh River, Kordestan, Iran. Minimizing wastewater treatment plant (WWTP) costs, improving the EquityMeasure, and enhancing water quality index (WQI) of the river have been considered as objective functions of MPWLA problems. The applied WQI integrates various water quality parameters (biochemical oxygen demand (BOD), dissolved oxygen (DO), NH4-N, NO3-N, PO4-P, total suspended solids (TSS), and Coliform) in monitoring stations along the river. Results show in the scenario with the best EquityMeasure, higher pollutant removal rates have been allocated to Sanandaj WWTP effluent and pollutant point source No. 7 (creek of landfill leachate) due to their greater contributions to Gheshlagh River contamination. Owing to high pollutant load effluents and unsuitable background conditions in Gheshlagh River, more specific studies show that the water quality index may not be improved over 0.22, no matter how much cost is incurred or equity is sacrificed.

Waste load allocation for water quality management of a heavily polluted river using linear programming

2003 ◽  
Vol 48 (10) ◽  
pp. 185-190 ◽  
Author(s):  
J.H. Cho ◽  
K.H. Ahn ◽  
W.J. Chung ◽  
E.M. Gwon
Keyword(s):  
Water Quality ◽  
Linear Programming ◽  
Quality Management ◽  
River Basin ◽  
Water Quality Management ◽  
Load Reduction ◽  
Waste Load Allocation ◽  
Transfer Coefficients ◽  
Allocation Model ◽  
Waste Load

A waste load allocation model using linear programming has been developed for economic water quality management. A modified Qual2e model was used for water quality calculations and transfer coefficients were derived from the calculated water quality. This allocation model was applied to the heavily polluted Gyungan River, located in South Korea. For water quality management of the river, two scenarios were proposed. Scenario 1 proposed to minimise the total waste load reduction in the river basin. Scenario 2 proposed to minimise waste load reduction considering regional equity. Waste loads, which have to be reduced at each sub-basin and WWTP, were determined to meet the water quality goal of the river. Application results of the allocation model indicate that advanced treatment is required for most of the existing WWTPs in the river basin and construction of new WWTPs and capacity expansion of existing plants are necessary. Distribution characteristics of pollution sources and pollutant loads in the river basin was analysed using Arc/View GIS.

scholarly journals Fuzzy Optimization Model for Waste Load Allocation in a River with Total Maximum Daily Load (TMDL) Planning

Water ◽  
2020 ◽  
Vol 12 (9) ◽  
pp. 2618
Author(s):  
Jae Heon Cho ◽  
Jong Ho Lee
Keyword(s):  
Water Quality ◽  
Wastewater Treatment ◽  
Water Quality Management ◽  
Fuzzy Optimization ◽  
Fuzzy Model ◽  
Low Flow ◽  
Satisfaction Level ◽  
Waste Load Allocation ◽  
Pollutant Load ◽  
Waste Load

In traditional waste load allocation (WLA) decision making, water quality-related constraints must be satisfied. Fuzzy models, however, can be useful for policy makers to make the most reasonable decisions in an ambiguous environment, considering various surrounding environments. We developed a fuzzy WLA model that optimizes the satisfaction level by using fuzzy membership functions and minimizes the water quality management cost for policy decision makers considering given environmental and socioeconomic conditions. The fuzzy optimization problem was formulated using a max–min operator. The fuzzy WLA model was applied to the Yeongsan River basin, which is located in the southwestern part of the Korean Peninsula and Korean TMDLs were applied. The results of the fuzzy model show that the pollutant load reduction should be increased in the Gwangju 1 and Gwangju 2 wastewater treatment plants (WWTPs) and in subcatchments with high pollutant load. In particular, it is necessary to perform advanced wastewater treatment to decrease the load of 932 kg ultimate biochemical oxygen demand (BODu)/day in the large-capacity Gwangju 1 WWTP and reduce the BODu emission concentration from 4.3 to 2.7 mg/L during the low-flow season. The satisfaction level of the fuzzy model is a relatively high at 0.81.

Sign in / Sign up

Export Citation Format

Share Document